Efficient real-time face detection for high resolution surveillance applications

This paper presents an efficient face detection method suitable for real-time surveillance applications. Improved efficiency is achieved by constraining the search window of an AdaBoost face detector to pre-selected regions. Firstly, the proposed method takes a sparse grid of sample pixels from the image to reduce whole image scan time. A fusion of foreground segmentation and skin colour segmentation is then used to select candidate face regions. Finally, a classifier-based face detector is applied only to selected regions to verify the presence of a face (the Viola-Jones detector is used in this paper). The proposed system is evaluated using 640 x 480 pixels test images and compared with other relevant methods. Experimental results show that the proposed method reduces the detection time to 42 ms, where the Viola-Jones detector alone requires 565 ms (on a desktop processor). This improvement makes the face detector suitable for real-time applications. Furthermore, the proposed method requires 50% of the computation time of the best competing method, while reducing the false positive rate by 3.2% and maintaining the same hit rate.

Behavioral biometrics for persistent single sign-on

Driven by the rapid development of ubiquitous and pervasive computing, personalized services and applications are deployed to support our lives. Accordingly, the number of interfaces and devices (smartphone, tablet computer, etc.) provided to access and consume these services is growing continuously. To simplify the complexity of managing many accounts with different credentials, Single Sign-On (SSO) solutions have been introduced. However, a single password for many accounts represents a single-point-of-failure. Furthermore, once initiated SSO session is a high potential risk when the working station is left unlocked and unattended. In this paper, we present a conception of a Persistent Single Sign-On (PSSO) for ubiquitous home environments by involving the capabilities of Behavioral Biometrics to check the identity of the user continuously in an unobtrusive manner.

Continuous and non-intrusive identity verification in real-time environments based on free-text keystroke dynamics

Internet services are important part of daily activities for most of us. These services come with sophisticated authentication requirements which may not be handled by average Internet users. The management of secure passwords for example creates an extra overhead which is often neglected due to usability reasons. Furthermore, password-based approaches are applicable only for initial logins and do not protect against unlocked workstation attacks. In this paper, we provide a non-intrusive identity verification scheme based on behavior biometrics where keystroke dynamics based-on free-text is used continuously for verifying the identity of a user in real-time. We improved existing keystroke dynamics based verification schemes in four aspects. First, we improve the scalability where we use a constant number of users instead of whole user space to verify the identity of target user. Second, we provide an adaptive user model which enables our solution to take the change of user behavior into consideration in verification decision. Next, we identify a new distance measure which enables us to verify identity of a user with shorter text. Fourth, we decrease the number of false results. Our solution is evaluated on a data set which we have collected from users while they were interacting with their mail-boxes during their daily activities.

Collective sampling and analysis of high order tensors for chatroom communications

This work investigates the accuracy and efficiency tradeoffs between centralized and collective (distributed) algorithms for (i) sampling, and (ii) n-way data analysis techniques in multidimensional stream data, such as Internet chatroom communications. Its contributions are threefold. First, we use the Kolmogorov-Smirnov goodness-of-fit test to show that statistical differences between real data obtained by collective sampling in time dimension from multiple servers and that of obtained from a single server are insignificant. Second, we show using the real data that collective data analysis of 3-way data arrays (users x keywords x time) known as high order tensors is more efficient than centralized algorithms with respect to both space and computational cost. Furthermore, we show that this gain is obtained without loss of accuracy. Third, we examine the sensitivity of collective constructions and analysis of high order data tensors to the choice of server selection and sampling window size. We construct 4-way tensors (users x keywords x time x servers) and analyze them to show the impact of server and window size selections on the results.

Non-intrusive continuous user behaviour analysis using computerized systems

There are different ways to authenticate humans, which is an essential prerequisite for access control. The authentication process can be subdivided into three categories that rely on something someone i) knows (e.g. password), and/or ii) has (e.g. smart card), and/or iii) is (biometric features). Besides classical attacks on password solutions and the risk that identity-related objects can be stolen, traditional biometric solutions have their own disadvantages such as the requirement of expensive devices, risk of stolen bio-templates etc. Moreover, existing approaches provide the authentication process usually performed only once initially. Non-intrusive and continuous monitoring of user activities emerges as promising solution in hardening authentication process: iii-2) how so. behaves. In recent years various keystroke dynamic behavior-based approaches were published that are able to authenticate humans based on their typing behavior. The majority focuses on so-called static text approaches, where users are requested to type a previously defined text. Relatively few techniques are based on free text approaches that allow a transparent monitoring of user activities and provide continuous verification. Unfortunately only few solutions are deployable in application environments under realistic conditions. Unsolved problems are for instance scalability problems, high response times and error rates. The aim of this work is the development of behavioral-based verification solutions. Our main requirement is to deploy these solutions under realistic conditions within existing environments in order to enable a transparent and free text based continuous verification of active users with low error rates and response times.

Multipurpose identity-based signcryption : a Swiss army knife for identity-based cryptography

Identity-Based (IB) cryptography is a rapidly emerging approach to public-key cryptography that does not require principals to pre-compute key pairs and obtain certificates for their public keys— instead, public keys can be arbitrary identifiers such as email addresses, while private keys are derived at any time by a trusted private key generator upon request by the designated principals. Despite the flurry of recent results on IB encryption and signature, some questions regarding the security and efficiency of practicing IB encryption (IBE) and signature (IBS) as a joint IB signature/encryption (IBSE) scheme with a common set of parameters and keys, remain unanswered. We first propose a stringent security model for IBSE schemes. We require the usual strong security properties of: (for confidentiality) indistinguishability against adaptive chosen-ciphertext attacks, and (for nonrepudiation) existential unforgeability against chosen-message insider attacks. In addition, to ensure as strong as possible ciphertext armoring, we also ask (for anonymity) that authorship not be transmitted in the clear, and (for unlinkability) that it remain unverifiable by anyone except (for authentication) by the legitimate recipient alone. We then present an efficient IBSE construction, based on bilinear pairings, that satisfies all these security requirements, and yet is as compact as pairing-based IBE and IBS in isolation. Our scheme is secure, compact, fast and practical, offers detachable signatures, and supports multirecipient encryption with signature sharing for maximum scalability.

Indigenous knowledge and IP food security : a review of concepts and cases

Dáwat, Pamahándí, Tawíd, Ságda, Lampísa, Ibabások, Lapát, Panedlák: for most of us gathered here, these are words that we don’t usually use in our daily lives. Others may consider them as exotic, alien, funny and even backward. However, for indigenous kindred among us, these words denote an intimate identity and deep understanding of the world around them. It constitutes a broader knowledge system, be written or otherwise, which guides them in the management of resources within their ancestral land. This paper will provide a brief theoretical framework of the concepts of indigenous knowledge systems—hereinafter called IKS, and indigenous peoples food security, and hopefully a deeper or continued appreciation in the study of both concepts in general.

Security analysis of linearly filtered NLFSRs

Non-linear feedback shift register (NLFSR) ciphers are cryptographic tools of choice of the industry especially for mobile communication. Their attractive feature is a high efficiency when implemented in hardware or software. However, the main problem of NLFSR ciphers is that their security is still not well investigated. The paper makes a progress in the study of the security of NLFSR ciphers. In particular, we show a distinguishing attack on linearly filtered NLFSR (or LF-NLFSR) ciphers. We extend the attack to a linear combination of LF-NLFSRs. We investigate the security of a modified version of the Grain stream cipher and show its vulnerability to both key recovery and distinguishing attacks.

Plaintext awareness in identity-based key encapsulation

The notion of plaintext awareness ( PA ) has many applications in public key cryptography: it offers unique, stand-alone security guarantees for public key encryption schemes, has been used as a sufficient condition for proving indistinguishability against adaptive chosen-ciphertext attacks ( IND-CCA ), and can be used to construct privacy-preserving protocols such as deniable authentication. Unlike many other security notions, plaintext awareness is very fragile when it comes to differences between the random oracle and standard models; for example, many implications involving PA in the random oracle model are not valid in the standard model and vice versa. Similarly, strategies for proving PA of schemes in one model cannot be adapted to the other model. Existing research addresses PA in detail only in the public key setting. This paper gives the first formal exploration of plaintext awareness in the identity-based setting and, as initial work, proceeds in the random oracle model. The focus is laid mainly on identity-based key encapsulation mechanisms (IB-KEMs), for which the paper presents the first definitions of plaintext awareness, highlights the role of PA in proof strategies of IND-CCA security, and explores relationships between PA and other security properties. On the practical side, our work offers the first, highly efficient, general approach for building IB-KEMs that are simultaneously plaintext-aware and IND-CCA -secure. Our construction is inspired by the Fujisaki-Okamoto (FO) transform, but demands weaker and more natural properties of its building blocks. This result comes from a new look at the notion of γ -uniformity that was inherent in the original FO transform. We show that for IB-KEMs (and PK-KEMs), this assumption can be replaced with a weaker computational notion, which is in fact implied by one-wayness. Finally, we give the first concrete IB-KEM scheme that is PA and IND-CCA -secure by applying our construction to a popular IB-KEM and optimizing it for better performance.

The impact of personal identity and intimacy on the use of social media

Personal identity and intimacy levels change over time and this can influence the way consumers buy and use goods and services. This thesis examined how levels of personal identity and intimacy influence the use of social media by consumers of different ages. A survey of 208 users of facebook demonstrated that consumers with weak levels of personal identity use social media to increase their identity and popularity, while consumers with strong levels of personal identity use social media for self-expression. Consumers with high intimacy levels use social media for socian connection and social investigation.

Security metrics for Java bytecode programs

Although there are many approaches for developing secure programs, they are not necessarily helpful for evaluating the security of a pre-existing program. Software metrics promise an easy way of comparing the relative security of two programs or assessing the security impact of modifications to an existing one. Most studies in this area focus on high level source code but this approach fails to take compiler-specific code generation into account. In this work we describe a set of object-oriented Java bytecode security metrics which are capable of assessing the security of a compiled program from the point of view of potential information flow. These metrics can be used to compare the security of programs or assess the effect of program modifications on security using a tool which we have developed to automatically measure the security of a given Java bytecode program in terms of the accessibility of distinguished ‘classified’ attributes.

Efficient selective identity-based encryption without random oracles

We construct two efficient Identity-Based Encryption (IBE) systems that admit selective-identity security reductions without random oracles in groups equipped with a bilinear map. Selective-identity secure IBE is a slightly weaker security model than the standard security model for IBE. In this model the adversary must commit ahead of time to the identity that it intends to attack, whereas in an adaptive-identity attack the adversary is allowed to choose this identity adaptively. Our first system—BB1—is based on the well studied decisional bilinear Diffie–Hellman assumption, and extends naturally to systems with hierarchical identities, or HIBE. Our second system—BB2—is based on a stronger assumption which we call the Bilinear Diffie–Hellman Inversion assumption and provides another approach to building IBE systems. Our first system, BB1, is very versatile and well suited for practical applications: the basic hierarchical construction can be efficiently secured against chosen-ciphertext attacks, and further extended to support efficient non-interactive threshold decryption, among others, all without using random oracles. Both systems, BB1 and BB2, can be modified generically to provide “full” IBE security (i.e., against adaptive-identity attacks), either using random oracles, or in the standard model at the expense of a non-polynomial but easy-to-compensate security reduction.

Distributed public-key cryptography from weak secrets

We introduce the notion of distributed password-based public-key cryptography, where a virtual high-entropy private key is implicitly defined as a concatenation of low-entropy passwords held in separate locations. The users can jointly perform private-key operations by exchanging messages over an arbitrary channel, based on their respective passwords, without ever sharing their passwords or reconstituting the key. Focusing on the case of ElGamal encryption as an example, we start by formally defining ideal functionalities for distributed public-key generation and virtual private-key computation in the UC model. We then construct efficient protocols that securely realize them in either the RO model (for efficiency) or the CRS model (for elegance). We conclude by showing that our distributed protocols generalize to a broad class of “discrete-log”-based public-key cryptosystems, which notably includes identity-based encryption. This opens the door to a powerful extension of IBE with a virtual PKG made of a group of people, each one memorizing a small portion of the master key.

Analysis of bilinear pairing-based accumulator for identity escrowing

An accumulator based on bilinear pairings was proposed at CT-RSA'05. Here, it is first demonstrated that the security model proposed by Lan Nguyen does lead to a cryptographic accumulator that is not collision resistant. Secondly, it is shown that collision-resistance can be provided by updating the adversary model appropriately. Finally, an improvement on Nguyen's identity escrow scheme, with membership revocation based on the accumulator, by removing the trusted third party is proposed.